1. Field of the Invention
The present invention relates, in general, to an image processing and biometric recognition technique. In particular, the present invention is a system and method for representing an iris image to enhance the recognition technique.
2. Description of the Related Art
A biometric recognition system operates by acquiring biometric data from an individual, extracting a feature set from the acquired data, and comparing this feature set against a template set in a database. The most common biometric data that prior art biometric recognition systems acquire include fingerprints, retinas, voice, and iris. Since the iris has the unique characteristic of very little variation over an individual's life and a multitude of variation between individuals, iris detection is one of the most accurate and secure means of biometric identification. Furthermore, since iris-based recognition systems have become more user-friendly, iris detection is not only one of the least invasive detection methods, but also cost-effective.
The prior art describes capturing an image of an eye and analyzing the image to produce an iris code. The prior art does not describe locating the iris in an image of an eye and representing the iris as a one-dimensional signal or iris string as disclosed herein. The prior art also does not describe using the iris string for feature extraction, encoding, and matching.
Iris recognition to identify a subject, such as a human, animal, or the like, has been proposed for more than 20 years and has been the subject of numerous prior art publications. The prior art includes many detailed illustrations of the idea about how to set up equipment for iris acquisition. This is a factor in practical iris recognition system because the iris is a very small area to detect in comparison to a face. The subject's face can be captured very easily and non-intrusively, but if we want to capture an iris image, the task became not so trivial. Therefore, how to setup the cameras and the lighting in order to capture a high quality iris image is an important factor. The prior art also describe the adoption of a digitalized controlled circuit where the camera and lighting are all controlled by a central processing unit. The prior art further proposes a new way of capturing an iris image so that there is no need to position the camera very close to the subjects, which greatly enhances the usability of iris recognition system in many practical situations. For iris segmentation work, the prior art only describes the use of a boundary detection algorithm or edge detection algorithm to localize the pupil. The prior art describes first finding the limbic boundary and pupil boundary, and at last, localize the eyelid boundary. However, the prior art does not describe how to match two irises and produce a score of likeness, and how much confidence can be based on the chosen threshold. The prior art only provides exemplary algorithms that may perform well in iris recognition, for example, the well-known Fisher LDA algorithm. The prior art also does not provide a substantial statistical analysis about how good iris recognition can perform in turns of False Acceptance Rate (FAR) and False Reject Rate (FRR).
However, the prior art does not describe how to capture the iris image in order to achieve such high recognition results. The prior art does not describe how good the iris image has to be in order to produce a clear iris code which can represent every detail in the iris pattern. Furthermore, the prior art describes methods to achieve such high quality iris images that involve the subject sitting on a chair, putting their head on a wooden rack, and keeping their eyes wide open while the camera takes the picture. This prior art method of iris acquisition will drastically reduce the practicality of the iris recognition system.
The prior art demonstrates that high quality iris acquisition gives results of good biometric matching, but reduces the practicality of the system. However, systems that can capture iris images in non-intrusive manners usually reduce the iris image quality and inevitably downgrade the iris recognition performance. The iris image quality and the ease of use of the iris acquisition system are important factors for a successful biometric identification system; yet it seems that they are two factors usually system designers have to tune to trade them off. The present invention of image enhancement technology acquires super high-resolution iris images while restricted conditions for the subjects are minimized during iris acquisition stage. The present invention achieves both of these goals (high quality iris image and the friendliness of the system), while also achieving high performance of iris recognition system.